Paper
9 October 2023 Deep-learning enables classification and regression of polarization singularities
Yaqi Wang, Fu Feng, Huimin Hu, Bo Zhao, Zefeng Guo, Jiaan Gan, Nannan Li
Author Affiliations +
Proceedings Volume 12791, Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023); 127912F (2023) https://doi.org/10.1117/12.3004976
Event: Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023), 2023, Qingdao, SD, China
Abstract
Due to their wide applications in imaging, display and optical communication, polarization singularities detection has become an inescapable task in these fields. However, because of the noise and turbulence imposed during the transmission of polarization information, traditional methodologies have difficulty in recognizing the disturbed polarization state effectively. The received polarization information may be de-correlated even the input polarization singularities are the same. Therefore, it remains a challenge to detect the polarization singularities in a fluctuated environment. In this work, we experimentally explore the potential of deep-learning in the classification and regression of polarization singularities. It has been demonstrated that this approach realizes the high accuracy of 98.89% in polarization singularity classification and gets low mean absolute error (MAE) ranges of ±0.021 in polarization singularity regression. The proposed approach proves the successful classification and regression of polarization singularities using deep learning methods.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yaqi Wang, Fu Feng, Huimin Hu, Bo Zhao, Zefeng Guo, Jiaan Gan, and Nannan Li "Deep-learning enables classification and regression of polarization singularities", Proc. SPIE 12791, Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023), 127912F (9 October 2023); https://doi.org/10.1117/12.3004976
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KEYWORDS
Polarization

Speckle pattern

Correlation coefficients

Education and training

Spatial light modulators

Terrain classification

Data transmission

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